Concealed Personally Familiar Face Detection with EEG in Rapid Serial Visual Presentation

Classical concealed information tests (CITs) can in some circumstances detect concealed information, but are vulnerable to countermeasures that participants can use to evade detection. Rapid serial visual presentation (RSVP) has demonstrated effectiveness against such countermeasures and can thus significantly reduce type-II errors. This study examined the effectiveness of an RSVP-based CIT combined with EEG in detecting ‘concealed knowledge’ of personally familiar faces. We compared the sensitivity of traditional univariate analyses, regional multichannel analyses and multivariate decoding analyses. A total of 29 participants performed an RSVP task in which they searched for a target face while a personally familiar face (one of their parents), or one of two control faces appeared in the stream. Using univariate cluster-based permutation tests on the P300 and P600 components at Pz, personally familiar faces were detected in 18 out of 29 participants, yielding a detection rate of 62.1%. Additionally, increased theta power was observed in response to personally familiar faces, allowing detection in 14 participants (48.3%). Regional multichannel analyses indicated that Pz and surrounding electrodes exhibited the largest familiarity effect, successfully detecting 13 participants (44.8%). Multivariate decoding analyses detected personally familiar faces at the group level, though individual variability remained high. It suggests that multivariate decoding is promising but requires larger datasets than traditional analyses and should focus on central and frontal electrodes to avoid the influence of low-level visual features. Overall, our results highlight the potential of RSVP-based CIT as an effective tool when paired with an optimized EEG experimental paradigms and data-analysis techniques.